LeddarTech Obtains Series D Funding and Debt Facility to Scale Sensor Fusion

LeddarTech provides lidar technologies and software to automotive manufacturers and suppliers to enable autonomy.

LeddarTech


Street view with the LeddarVision sensor-fusion and perception system.
LeddarTech plans to use the $140 million investment to support growth and development efforts for its proprietary perception technologies for automotive manufacturers.

Investors and innovators are working to make smart and self-driving cars more perceptive. LeddarTech today announced that it has raised $140 million (U.S.), including a first Series D close of $116 million and debt facility of $24 million. The Quebec City-based company said it plans to use the funding to accelerate the development and commercialization of its sensing technologies.

​​​​​​“The success of this round is a testament to the growth and industry recognition LeddarTech has achieved,” stated Charles Boulanger, CEO of LeddarTech.

The company also said it will use its latest investment to augment engineering resources so it can meet the demands from global OEM and Tier 1 and 2 automotive customers. LeddarTech claimed that its sensor systems are the most flexible, roboust, and accurate ones available.

LeddarVision supports automotive suppliers

Founded in 2007, LeddarTech offers the LeddarVision raw-data sensor fusion and perception platform. It generates a 3D environmental model with multi-sensor configurations to support SAE Level 2 to Level 5 autonomy.

In addition, the company supports lidar makers and automotive system integrators with LeddarSteer, a digital beam-steering device. It also provides the LiDAR XLRator system for automotive-grade, solid-state lidar development based on LeddarEngine and core components from global semiconductor partners.

LeddarTech said it has more than 100 granted or pending patents for advanced driver-assist systems (ADAS) and autonomous driving (AD).

Canadian investors validate LeddarTech approach

FS Investors led LeddarTech's financing round. Participants included Investissement Québec, BDC Capital, Go Capital, certain funds managed by Fidelity Investments Canada ULC, Fonds de solidarité FTQ, Export Development Canada, ams OSRAM, Desjardins Capital, UI Investissement, Cowen Investment II LLC and other LeddarTech management.

“Our decision to partner with LeddarTech began with our introduction to the corporate senior management team,” said Nick Stone, founder and partner of FS Investors. “Individually, the senior team possess decades of experience in the technology industry. In addition, many have worked with major global automotive and sensing technology companies.”

“An extensive due-diligence process, coupled with strong customer validation, confirmed that LeddarTech’s unique solution is the best positioned in the market to unlock mass adoption of ADAS and AD by breaking typical software dependency on hardware in sensing,” he added. “LeddarVision provides customers with the flexibility to quickly scale across vehicle models and deliver faster to market with greater performance at a lower cost.”

“I am delighted to welcome FS Investors as our most recent investors, who bring vast experience and expertise in the deep tech sector,” Boulanger said. “Our team and I look forward to working with FS Investors, our other new investors, and our existing partners to enable our customers to significantly deploy our reliable and cost-effective ADAS and AD solutions across their brands and markets.”

The debt facility was secured with Desjardins Group. Cowen and Desjardins Capital Markets acted as co-advisors in this investment round.

This state-of-the-art solution enables the detection of the various objects in the scene, including vehicles, pedestrians, bicycles, drivable road, obstacles, signs, lanes, lane lines and more. LeddarVision also detects very small obstacles on the road with better detection rates and fewer false alarms than legacy “object fusion” solutions.

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LeddarTech

Street view with the LeddarVision sensor-fusion and perception system.


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